Tianjin Zhongshui Science and Technology Consulting Co.

Tianjin, China

Tianjin Zhongshui Science and Technology Consulting Co.

Tianjin, China
SEARCH FILTERS
Time filter
Source Type

Li F.,Tianjin University | Cao R.,Tianjin University | Zhao Y.,Beijing Institute of Water | Mu D.,Tianjin Zhongshui Science and Technology Consulting Co. | And 2 more authors.
Theoretical and Applied Climatology | Year: 2015

A new method for calculating evaporation is proposed, using the Penman–Monteith (P-M) model with remote sensing. This paper achieved the effective estimation to daily evapotranspiration in the Ziya river catchment by using the P-M model based on MODIS remote sensing leaf area index and respectively estimated plant transpiration and soil evaporation by using coefficient of soil evaporation. This model divided catchment into seven different sub-regions which are prairie, meadow, grass, shrub, broad-leaved forest, cultivated vegetation, and coniferous forest through thoroughly considering the vegetation diversity. Furthermore, optimizing and calibrating parameters based on each sub-region and analyzing spatio-temporal variation rules of the model main parameters which are coefficient of soil evaporation f and maximum stomatal conductance gsx. The results indicate that f and gsx calibrated by model are basically consistent with measured data and have obvious spatio-temporal distribution characteristics. The monthly average evapotranspiration value of simulation is 37.96 mm/mon which is close to the measured value with 33.66 mm/mon and the relative error of simulation results in each subregion are within 11 %, which illustrates that simulated values and measured values fit well and the precision of model is high. In addition, plant transpiration and soil evaporation account for about 84.64 and 15.36 % respectively in total evapotranspiration, which means the difference between values of them is large. What is more, this model can effectively estimate the green water resources in basin and provide effective technological support for water resources estimation. © 2015 Springer-Verlag Wien


There is a close relationship between groundwater level in a shallow aquifer and the surface ecological environment; hence, it is important to accurately simulate and predict the groundwater level in eco-environmental construction projects. The multiple linear regression (MLR) model is one of the most useful methods to predict groundwater level (depth); however, the predicted values by this model only reflect the mean distribution of the observations and cannot effectively fit the extreme distribution data (outliers). The study reported here builds a prediction model of groundwater-depth dynamics in a shallow aquifer using the quantile regression (QR) method on the basis of the observed data of groundwater depth and related factors. The proposed approach was applied to five sites in Tianjin city, north China, and the groundwater depth was calculated in different quantiles, from which the optimal quantile was screened out according to the box plot method and compared to the values predicted by the MLR model. The results showed that the related factors in the five sites did not follow the standard normal distribution and that there were outliers in the precipitation and last-month (initial state) groundwater-depth factors because the basic assumptions of the MLR model could not be achieved, thereby causing errors. Nevertheless, these conditions had no effect on the QR model, as it could more effectively describe the distribution of original data and had a higher precision in fitting the outliers. © 2016 Springer-Verlag Berlin Heidelberg


Zhang J.,Zhengzhou University | Zhao Y.,China Institute of Water Resources and Hydropower Research | Ding Z.,Tianjin Zhongshui Science and Technology Consulting Co.
Paddy and Water Environment | Year: 2016

The relationship between rainfall and reference crop evapotranspiration (ET0) can be complex in an irrigation district. To reveal such complex and possibly a nonlinear relationship, rainfall and ET0 data were collected at the Xinxiang irrigation experiment station from the years 1961 to 2010. Marginal distributions of the two variables derived from fitting the Pearson Type III distribution were incorporated for the development of the joint probability distribution using a copula model. Subsequently, the joint probability as well as the return period of given specific rainfall and ET0 values can be computed. For the analysis of the variations in drought conditions over the 50 years, the copula-based joint probability is further decomposed into several subcomponents using the empirical mode decomposition method. The variations under distinct frequencies and over different time periods were observed. Our results showed that the joint probability distribution of rainfall and ET0 can facilitate the planning for drought resistance in an irrigation district. © 2016 The International Society of Paddy and Water Environment Engineering and Springer Japan


Zhang J.,Zhengzhou University | Ding Z.,Tianjin Zhongshui Science and Technology Consulting Co. | Yuan W.,Zhengzhou University | Zuo Q.,Zhengzhou University
Paddy and Water Environment | Year: 2013

Limited by Fourier analysis and the selection of different wavelet base functions, the wavelet analysis method shows some deficiencies. For that reason, the empirical mode decomposition method is applied to analyze fluctuating periods and local features of annual rainfall and reference crop evapotranspiration (ET0) from 1959 to 2002. With respect to the correlation between variables, the traditional time series analysis methods often assume that data sequences are stationary which result in "spurious regression." Therefore, the cointegration theory is introduced to describe the long-term equilibrium relationship of rainfall and ET0. At last, to understand the uncertainty between these two variables, the set pair analysis (SPA) method is used to present the identity, discrepancy, and contrary of rainfall and ET0 with multi-time scales. The results reveal that rainfall and ET0 have a complex relationship which may be related to El Nino, air-sea intersection, solar activity. Moreover, the fluctuation periods of rainfall and ET0 also have similar short and middle period level, and slightly different long period level. The changes of rainfall and ET0 present mainly the contrary and the discrepancy. This relationship will remain a long-term equilibrium. © 2012 Springer-Verlag.


Zhang J.,Zhengzhou University | Guo B.,YELLOW AND CO | Ding Z.,Tianjin Zhongshui Science and Technology Consulting Co.
Environmental Monitoring and Assessment | Year: 2013

The empirical mode decomposition method is applied to analyze fluctuating periods and local features of the annual drought index and the drought index in the irrigation and non-irrigation periods from 1956 to 2010 in the Yinchuan irrigation district. In order to understand the uncertainty between these variables, the set pair analysis method is used to present the identity, discrepancy, and contrary of the drought index with multi-time scales. The results reveal that the annual drought index and the drought index in the irrigation and non-irrigation periods have a complex relationship which may be related to El Niño, the air-sea intersection, and the long period of solar activity. The drought index in the irrigation and non-irrigation periods presents mainly the contrary and the discrepancy; the fluctuating shapes of the annual drought index and drought index in the irrigation period are the same on their different period levels. The original annual drought index and its intrinsic mode function components have a certain connection degree; they mainly present the discrepancy. © 2013 Springer Science+Business Media Dordrecht.


Zhang J.,Zhengzhou University | Zhao Y.,China Institute of Water Resources and Hydropower Research | Ding Z.,Tianjin Zhongshui Science and Technology Consulting Co.
Water Resources Management | Year: 2014

Rainfall and grain yield are two closely related random variables to be worthy of studying. The meteorological yield explains the influences of weather changes on grain yield. Based on the data series from 1980 to 2006 in Jinghuiqu irrigation district of Shaanxi Province in China, the meteorological yield is achieved from grain yield. Then, the empirical mode decomposition method is applied to analyze fluctuating periods and local features of rainfall and meteorological yield. Meanwhile, the copula method is introduced into describe the joint probability distribution of rainfall and meteorological yield. The studied results show that rainfall and meteorological yield exist vary fluctuation periods with multi-time scales, including 2 to 4 years of short period level, 4 to 6 (or 7) years of middle period level and 19 (or 10 to 11) years of long period level. Using the frank copula method, the bivariate distribution and return period of rainfall and meteorological yield was successfully developed to reveal the encounter risk of their different magnitudes. Finally, similarly with rainfall and meteorological yield, the complex changes and fluctuation periods are also proven to be existed in their joint probability. © 2014 Springer Science+Business Media Dordrecht.


Zhang J.,Zhengzhou University | Ding Z.,Tianjin Zhongshui Science and Technology Consulting Co | Guo B.,YELLOW AND CO
Shuili Fadian Xuebao/Journal of Hydroelectric Engineering | Year: 2015

Runoff and sediment conditions of the Jinghe River were categorized into rich, normal and poor states, by using a P-III-type distribution and the data series at Zhangjiashan hydrological station from 1932 to 2008, and the evolution trend of runoff-sediment combination (RSC) was examined by the theory of Markov processes. An analysis of transient probability shows that the combinations tend to be rich-rich or poor-poor. In synchronous self-transient probability, rich-rich combination is the most probable with a value of 0.72, while in asynchronous self-transient probability, normal-poor is the most probable with a value of 0.50, and the synchronous-asynchronous transient probability of poor-normal combination is greater. An analysis of RSC encounter risks with the Copula method reveals that rich-rich encounter risk is the highest value of 27.9% in synchronous frequency, but differences exist in asynchronous ones. In general, the synchronous encounter frequencies are higher than the asynchronous ones. Finally, an analysis on the recurrence period of RSC is presented. ©, 2014, 10031243 Tsinghua University Press. All right reserved.

Loading Tianjin Zhongshui Science and Technology Consulting Co. collaborators
Loading Tianjin Zhongshui Science and Technology Consulting Co. collaborators